POSTECH Scientists Research RNA Polymerase Contribution to Gene Expression, Published in Nature Communications
Noise plays a key role in important biological processes, such as bacterial antibiotics resistance, cancer development, and stem cell differentiation. Physics can explain much of this biological phenomenon.
Professor Nam Ki Lee of the Department of Physics and the School of Interdisciplinary Bioscience and Bioengineering with Department of Physics graduate students Sora Yang, Seunghyeon Kim, Cheolhee Kim, Hyeong Jeon An and Professor Jaeyoung Sung of Chung-Ang University studied how cells propagate noise using RNA polymerase. Their research was published in this month’s Nature Communications journal.
The uncertainty, a common concept in physics, exists in living cells because all biological processes are governed by a stochastic chemical reaction. Even genetically identical cells exhibit remarkable diversity in protein expression level, which is termed a cell-to-cell variation or noise. Noise may significantly contribute to the difference even between identical twins. Recent studies show that noise plays crucial functional roles in cells, such as state switching, differentiation, and cell fate determination.
However, the origin of protein expression noise has not yet been addressed. Especially, concentration variation of RNA polymerase (RNAP), a key machinery performing transcription, has been viewed to be one of the major noise sources. How RNAP generates or regulates noise has not been investigated yet because this protein is an essential factor for cell growth.
This is the first study to demonstrate that transcription, a process of generating mRNA, is one of the major noise sources. The research team proposed a new model of how RNAP concentration variation propagates to protein expression noise.
In the study, the research team used T7 RNAP to control the RNAP concentration in livingEscherichia coli (E.coli) cells. As a result, how the variation of RNAP concentration effects on the protein expression noise was successfully addressed. In the future, these findings may contribute to interpret many complex biological processes, which cannot be understood at a genomic level.
“Our approach can be applied to investigate the bacterial antibiotics resistance and to control the noise level in living cells, which was not possible before,” said Professor Lee. “The approach can also be applied to study the mechanism of the state transition of cells, such as cancer development and stem cell differentiation.”
The research was supported by the MSIP (Ministry of Science, ICT and Future Planning), Korea under the “IT Consilience Creative Program” (NIPA-2014-H0201-14-1001) supervised by NIPA (National IT Industry Promotion Agency).